Example systems, apparatus, and methods receive audio information including a plurality of frames from a source device, wherein each frame of the plurality of frames includes one or more audio samples and a time stamp indicating when to play the one or more audio samples of the respective frame. In an example, the time stamp is updated for each of the plurality of frames using a time differential value determined between clock information received from the source device and clock information associated with the device. The updated time stamp is stored for each of the plurality of frames, and the audio information is output based on the plurality of frames and associated updated time stamps. A number of samples per frame to be output is adjusted based on a comparison between the updated time stamp for the frame and a predicted time value for play back of the frame.

This disclosure relates to methods, non-transitory computer readable media, and systems that generate and visualize bias scores within segment-generation-user interfaces prior to executing proposed actions with regard to target segments. For example, the disclosed systems can generate a bias score indicating a measure of bias for a characteristic within a segment of users selected for a proposed action and visualize the bias score and corresponding characteristic in a segment-generation-user interface. In some implementations, the disclosed systems can further integrate detecting and visualizing bias as a bias score with selectable options for a segmentation-bias system to generate and modify segments of users to reduce detected bias.

Aspects of the present disclosure provide techniques for providing a graphical user interface. Embodiments include displaying a text input field. Embodiments include receiving an input of at least a portion of a tag via the text input field. Embodiments include displaying, in response to the input and proximate to the text input field, a graphical representation of an existing tag that relates to the input. The graphical representation includes a type of the existing tag, the existing tag, and a colored section on a right side or a left side of the graphical representation having a color that is associated with the type of the existing tag in the computing application. Embodiments include receiving a selection of the graphical representation and displaying an instance of the graphical representation inside of the text input field.

A method, apparatus and product for chat-based application interface for automation. Using a natural language interface, receiving user input. Based on the user input, determining an automation process of a computer program having a user interface (UI), to be executed. The automation process is executed by utilizing the UI to input data thereto or execute functionality thereof. Additionally or alternatively, a conversation to be implemented by a natural language interface may be defined. The conversation is configured to obtain from the user one or more values corresponding to one or more parameters. The conversation is associated with a parameterized automation process depending on the one or more parameters. The parameterized automation process is invoked automatically by a natural language interface and using one or more values provided by the user to the natural language interface for the one or more parameters.

A method includes displaying a user interface having a first region with one or more user interface elements and determining whether a shield is in a locked state or an unlocked state. The shield covers the first region when in the locked state and uncovers at least part of the first region when in the unlocked state. The method includes, in response to determining that the shield is in the locked state, displaying the shield covering the first region and disabling the user interface element(s). The method includes, in response to receiving user input on the shield while the shield is in the locked state, changing the shield to the unlocked state. Additionally, the method includes, in response to determining that the shield is in the unlocked state, displaying the first region such that the user interface element(s) is/are not covered by the shield and enabling the user interface element(s).

The present disclosure generally relates to managing access to credentials. In some examples, an electronic device authorizes release of credentials for use in an operation for which authorization is required. In some examples, an electronic device causes display of one or more steps to be taken to enable an input device for user input. In some examples, an electronic device disambiguates between commands to change the account that is actively logged-in on the device and commands to cause credentials to be released from the secure element.

The present disclosure generally relates to managing access to credentials. In some examples, an electronic device authorizes release of credentials for use in an operation for which authorization is required. In some examples, an electronic device causes display of one or more steps to be taken to enable an input device for user input. In some examples, an electronic device disambiguates between commands to change the account that is actively logged-in on the device and commands to cause credentials to be released from the secure element.

Systems and methods that provide audio feedback in response to gesture validity can provide a more intuitive interface that can train users to correctly complete gestures. Moreover, systems and methods that provide line-specific audio feedback can provide more specific feedback that can allow a user to better understand what sensing line is being contacted. The systems and methods can further include basing the audio feedback based at least in part on obtained activity data, such that invalid and valid feedbacks can provide different sounds dependent on the determined activity state.

Techniques are described for providing a ML data analytics application including guided ML workflows that facilitate the end-to-end training and use of various types of ML models, where such guided workflows may also be referred to as ML “experiments.” For example, the ML data analytics application may enable users to create experiments related to prediction of numeric fields (for example, using linear regression techniques), predicting categorical fields (for example, using logistic regression), detecting numerical outliers (for example, using various distribution statistics), detecting categorical outliers (for example, using probabilistic statistics), forecasting time series data, and clustering numeric events (for example, using k-means, density-based spatial clustering of applications with noise (DBSCAN), spectral clustering, or other techniques), among other possible uses of various types of ML models to analyze data.

Techniques are described for providing a ML data analytics application including guided ML workflows that facilitate the end-to-end training and use of various types of ML models, where such guided workflows may also be referred to as ML “experiments.” For example, the ML data analytics application may enable users to create experiments related to prediction of numeric fields (for example, using linear regression techniques), predicting categorical fields (for example, using logistic regression), detecting numerical outliers (for example, using various distribution statistics), detecting categorical outliers (for example, using probabilistic statistics), forecasting time series data, and clustering numeric events (for example, using k-means, density-based spatial clustering of applications with noise (DBSCAN), spectral clustering, or other techniques), among other possible uses of various types of ML models to analyze data.